For analysing the localized variation of power within a time range, we used the wavelet analysis technique. The periodogram provides the power spectral distribution as a function of frequency and the maximum peak in the power spectral distribution is considered as the frequency of the signal.
The first step to get the wavelet analysis is to find the Fourier transform of the given time series. This is followed with the selection and normalization of the function, which must have zero mean and localized in time and frequency space. Finally wavelet transform is calculated with the determination of the cone of influence and Fourier wavelength. The 95% confidence contours are choosen by assuming a background Fourier power spectrum ([1]}).
